Method and apparatus for two-stage planning

ABSTRACT

A plan through a space having a near field and a far field is determined. Using a sensor device, measurements of the far field are obtained and stored in an electronic memory. A processor uses the measurements to determine the viability of each far field plan among a plurality of candidate far field plans. The processor also determines a flexibility score for each of the candidate far field plans and selects a composite plan comprising the viable far field plan having a highest flexibility score among the viable candidate far field plans.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/521,291, filed Oct. 22, 2014, and entitled “METHOD AND APPARATUS FORTWO-STAGE PLANNING,” which is a continuation of U.S. patent applicationSer. No. 13/926,922, filed Jun. 25, 2013, and entitled “METHOD ANDAPPARATUS FOR TWO-STAGE PLANNING,” which claims benefit from U.S.Provisional Patent Application No. 61/800,424, filed Mar. 15, 2013, andentitled “METHOD AND SYSTEM FOR TWO-STAGE PLANNING,” both of which areexpressly incorporated by reference herein.

GOVERNMENT RIGHTS

This invention was made with government support under contract numberFA9453-06-D-0103 awarded by the United States Air Force. The governmenthas certain rights in the invention.

BACKGROUND OF THE INVENTION

1. Technical Field

The invention relates to route planning systems. More particularly, theinvention relates to a method and apparatus for two-stage route planningsystems.

2. Description of the Background Art

Route planning is critical for autonomous vehicles. For purposes of thediscussion herein, an autonomous vehicle, also known as a robotic car,or informally as driverless or self-driving, is a vehicle that s capableof fulfilling the human transportation capabilities of a traditionalvehicle. As an autonomous vehicle, it is capable of sensing itsenvironment and navigating without human input. Robotic cars existmainly as prototypes, but are likely to become more widespread in thenear future. Autonomous vehicles sense their surroundings with suchtechniques as radar, LIDAR, GPS, and computer vision. Advanced controlsystems interpret sensory information to identify appropriate navigationpaths, as well as obstacles and relevant signage. Some autonomousvehicles update their maps based on sensory input, allowing them to findtheir way through uncharted environments.

Since the late 2000s, significant advances have been made in bothtechnology and legislation relevant to autonomous vehicles. Numerousmajor companies and research organizations have developed workingprototype autonomous vehicles, including Google, Continental AutomotiveSystems, Bosch, Nissan, Toyota, Audi, and Oxford University. In June2011, the state of Nevada was the first jurisdiction in the UnitedStates to pass a law concerning the operation of autonomous vehicles.The Nevada law went into effect on Mar. 1, 2012.

It would be advantageous to provide a highly efficient and precise routeplanning system. Such system would be especially useful for autonomousvehicles, e.g. so-called self-driving or robotic vehicles.

SUMMARY OF THE INVENTION

A method and apparatus is provided for determining a plan through aspace having a near field and a far field. Using a sensor device,measurements of the far field are obtained and stored in an electronicmemory. A processor uses the measurements to determine the viability ofeach far field plan among a plurality of candidate far field plans. Theprocessor also determines a flexibility score for each of the candidatefar field plans and selects a composite plan comprising the viable farfield plan having a highest flexibility score among the viable candidatefar field plans.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a schematic representation of a roadway and apiecewise-linear roadway centerline according to the invention;

FIG. 2 shows a schematic representation of a smoothed roadway centerlineaccording to the invention;

FIG. 3 shows a schematic representation of roadway microlanes accordingto the invention;

FIG. 4 shows a near field and a far field along a roadway according tothe invention;

FIG. 5 shows a set of candidate vehicle maneuvers between microlanesaccording to the invention;

FIG. 6 shows a set of candidate vehicle trajectories along the roadwayof FIG. 3 according to the invention;

FIG. 7 shows a set of quantitative scores for the set of microlaneswithin the far field of the roadway of FIG. 3 according to theinvention;

FIG. 8 shows a flow chart summarizing the operation of a two-stageplanning method according to the invention; and

FIG. 9 is a block schematic diagram that depicts a machine in theexemplary form of a computer system within which a set of instructionsfor causing the machine to perform any of the herein disclosedmethodologies may be executed.

DETAILED DESCRIPTION OF THE INVENTION

Thus, a method and apparatus is provided for determining a plan througha space having a near field and a far field. Using a sensor device,measurements of the far field are obtained and stored in an electronicmemory. A processor uses the measurements to determine the viability ofeach far field plan among a plurality of candidate far field plans. Theprocessor also determines a flexibility score for each of the candidatefar field plans and selects a composite plan comprising the viable farfield plan having a highest flexibility score among the viable candidatefar field plans.

Embodiments of the invention concern a planning system and method fordetermining a plan through a space that is characterized by distinctnear and far domains. The invention is most readily understood withreference to a preferred embodiment in which a route planning systemnavigates an autonomous vehicle along a roadway.

While the invention is discussed herein in connection with pilotingautonomous vehicles along roadways, those skilled in the art willappreciate that the invention is not so limited, and that the inventionwill find use, for example, with human-operated vehicles, withinshipping and air lanes, and the like.

FIG. 1 shows a schematic representation of a roadway and apiecewise-linear roadway centerline according to the invention. A set ofvertices 122 define the end points of connected linear segments 121 thatapproximate the centerline between the physical edges 111 and 112, e.g.curbs or embankments, of the roadway. Typically, the route planningsystem receives this definition from an external data source, e.g. a GISdatabase containing roadway definitions for a particular region.

FIG. 2 shows a schematic representation of a smoothed roadway centerlineaccording to the invention. Generally, the smoothed roadway centerline210 rounds the corners of the piecewise-linear roadway centerline. Inone embodiment of the invention, the route planning system creates thesmoothed roadway centerline through the application of fillets oninterior corners and chamfers on exterior corners of radius R tangent toadjacent segments of the piecewise-linear roadway centerline.Alternatively, splines or other smoothing mechanisms can be used.Preferably, the radius R of the fillets and chamfers or a characteristicradius of the smoothing mechanism is based on the minimum capable orminimum desired turning radius of the vehicle.

FIG. 3 shows a schematic representation of roadway microlanes accordingto the invention. The microlanes are offset curves successivelyseparated from the smoothed roadway centerline by a distance d in adirection locally perpendicular to the centerline. FIG. 3 shows sevenmicrolanes 210-216, including the smoothed roadway centerline itself,but a larger or smaller number of microlanes may be used.

The route planning system uses the microlanes to determine a preferredforward trajectory on the roadway. As noted above, the navigationalmethod used by the route planning system is based on the definition oftwo planning regions, i.e. a near field and a far field.

FIG. 4 shows a near field and a far field along a roadway according tothe invention. The near field extends along the roadway from atransverse line through the position of the vehicle 500 at current timet₀ to a transverse line through the predicted position of the vehicle,based on current vehicle speed, at future time t₁. The far field extendsalong the roadway from the end of the near field to the predictedposition of the vehicle at future time t₂.

On account of its relative proximity to the vehicle, the near field ischaracterized by a high degree of fidelity in the measurements obtainedfrom sensors used to assess the vehicle's surroundings. In contrast, thefar field is characterized by a relatively low degree of fidelity insensor measurements.

In some embodiments of the invention a LIDAR unit, i.e. an opticalremote sensing device that can measure the distance to, or otherproperties of, targets by illuminating the target with laser light andanalyzing the backscattered light, is used for measurement. For example,the spatial resolution of distance measurements obtained from a LIDARunit with a fixed angular resolution is greater in the near field thanin the far field. In addition, the absolute precision in distancemeasurements, given a certain relative precision of the LIDAR unit, isgreater in the near field. Similarly, the spatial resolution of imagesobtained from onboard video cameras and the absolute precision ofdistances computed from a stereo correspondence between such images isgreater in the near field than in the far field.

For illustrative convenience, FIG. 4 shows the length of the near field,i.e. the distance between t₀ and t₁, as comparable to the length of thefar field, i.e. the distance between t₁ and t₂. In actual practice, thefar field may be substantially longer than the near field. For example,typical values for the times defining the regions may be t₁=2s andt₂=7s, implying time-lengths of the near and far fields of 2s and 5s,respectively. The precise values of t₁ and t₂ may be chosen based on thefidelity of the sensors and the reliability with which the vehicle cantrack a trajectory once determined.

FIG. 5 shows a set of candidate vehicle maneuvers between microlanesaccording to the invention. Each candidate maneuver is a transition inthe near field between the current microlane of the vehicle 500 and adestination microlane selected from among all microlanes, including thecurrent microlane. Preferably, each maneuver begins tangent to thecurrent microlane and ends tangent to the destination microlane. Forexample, in the roadway of FIG. 3, with the vehicle currently trackingthe center of seven microlanes, the set of candidate maneuvers includesthree rightward maneuvers 511, 513, 515, three leftward 512, 514, 516maneuvers, and one straight maneuver 510.

FIG. 6 shows a set of candidate vehicle trajectories along the roadwayof FIG. 3 according to the invention. Each trajectory comprises theunion of a near-field maneuver and a corresponding microlane in the farfield. For example, trajectory 562 comprises a leftward maneuver 532 inthe near field joined to microlane 212 in the far field at a destination552 along the transverse line corresponding to time t₁ demarcating theboundary between the near and far fields.

The route planning system evaluates each trajectory within the set ofcandidate trajectories to determine an optimal trajectory. Evaluationbegins with consideration of the near-field maneuvers. The routeplanning system eliminates from further consideration those trajectoriesthat begin with non-viable near-field maneuvers. For example, in FIG. 6,the route planning system discards the trajectories beginning withmaneuvers 535 and 536 because these maneuvers intersect the physicaledges 111 and 112 of the roadway at points 545 and 546. Similarly, theroute planning system can discard trajectories that begin with maneuverspassing through unacceptably hazardous obstacles or terrain featureswithin the near field. The route planning system then considers theremaining trajectories for quantitative scoring.

FIG. 7 shows a set of quantitative scores for the set of microlaneswithin the far field of the roadway of FIG. 3 according to theinvention. Scoring begins with an evaluation of the remainingtrajectories in the far field. Specifically, the route planning systemanalyzes the microlane of each remaining trajectory in the far field. Asnoted above, the fidelity of sensor measurements in the far field ispresumed to be low relative to sensor measurements in the near field.Thus, in the preferred embodiment, the route planning system attempts todetermine only whether each microlane is viable, i.e. specificallywhether each microlane contains or does not contain an obstacle orterrain feature that would render it impassable. In one embodiment ofthe invention, the route planning system calculates a scalartraversability score for each of the microlanes in the far field anddetermines that the microlane is passable if the traversability score isbelow above predetermined threshold. The traversability score may bebased upon, for example, the roughness of the roadway surface along themicrolane, the curvature of the microlane, and the presence or absenceof any obstacles along the microlane.

The route planning system assigns a score of 0 to each trajectorycomprising a microlane determined to be impassable in the far field,eliminating them from further consideration. For microlanes determinedto be passable in the far field, the route planning system assigns ascore equal to one greater than the number of adjacent microlanesbetween the microlane and the nearest impassable microlane or un-scoredmicrolane. The route planning system then selects the trajectoryincluding the microlane with the highest score and marks for executionthe near-field maneuver within the selected trajectory.

For example, in FIG. 7, the route planning system does not scoremicrolanes 215 and 216 because each comprises non-viable near-fieldmaneuvers, namely maneuvers 535 and 536 in FIG. 6. Microlane 211 isdetermined to be impassable on account of an obstacle 700 detected bythe sensors in the far field. Accordingly, the route planning systemassigns a score of 0 to microlane 211. Microlane 213 receives a score of1 because it is passable but no microlanes lie between it and thenearest impassable microlane 211 or un-scored microlane 215. Microlane210 also receives a score of 1 because it is passable but no microlaneslie between it and the nearest impassable microlane 211. Microlane 214also receives a score of 1 because it is passable but no microlanes liebetween it and the nearest un-scored microlane 216. Finally, microlane212 receives a score of 2 because it is passable and one microlane liesbetween it and each of the nearest impassable microlane 211 andun-scored microlane 216. Thus, in the example of FIG. 7, the routeplanning system selects the trajectory comprising the highest scoringmicrolane 212 and marks for execution the corresponding near fieldmaneuver 532.

In those instances when two or more microlanes share the highest score,the route planning system may select a trajectory, i.e. break the tie,by comparing quantitative costs of the near-field maneuvers. In oneembodiment of the invention, the route planning system uses sensormeasurements to discretely characterize the near-field terrain on a gridof cells. Each cell within the grid is evaluated using multiplecriteria. For example, using a scanning LIDAR, the route planning systemcan determine the height differential between the highest and lowestperimeter points of the cell, i.e. a slope calculation. The routeplanning system combines the multiple criteria to determine the maximumsafest speed at which the vehicle can traverse the cell. The cost of acell is inversely proportional to the speed determined. The cost of anear-field maneuver is proportional to the sum, along the maneuver, ofthe products of the cost of each cell and the length of the maneuverwithin that cell. Among the trajectories with far field microlanes withequal scores, the route planning system selects the trajectorycomprising the near-field maneuver with the lowest cost.

One skilled in the art will appreciate that many variations of theinvention are possible. As described above, when evaluating eachtrajectory in the far-field, the route planning system makes a Booleandetermination for each microlane; the microlane is determined to beeither passable or impassable and scores are computed for the microlanesbased on these Boolean values. In an alternative embodiment of theinvention, the route planning system uses the scalar traversabilityscore described above to compute the scores for each microlane.

As described above, each microlane determined to be impassable receivesa score of zero. For each passable microlane, the route planning systemassigns a score equal to the sum of the traversability score of themicrolane and

-   -   the combined leftward sum and rightward sum of traversability        scores, or    -   the minimum of the leftward sum and rightward sum of        traversability scores, or    -   the maximum of the leftward sum and rightward sum of        traversability scores.

The leftward sum of traversability scores is the sum of thetraversability scores of the microlanes between the microlane and thenearest leftward impassable or un-scored microlane. Similarly, therightward sum of traversability scores is the sum of the traversabilityscores of the microlanes between the microlane and the nearest rightwardimpassable or un-scored microlane.

As described above, the route planning system uses the costs computedfor the near-field maneuvers solely to select between trajectoriesincluding equally scored microlanes in the far field. In an alternativeembodiment of the invention, the route planning system combines thefar-field scores with the near-field costs to compute an overalldesirability of each trajectory. The relative weight assigned to thesetwo factors in computing the overall desirability can be adjusted tobalance the relative influence of the near- and far-field calculations.

Generally, though, as can be observed in the preferred embodiment, theroute planning system is designed to provide robust trajectories in theface of substantial sensor uncertainty in the far field. Given thisuncertainty, the route planning system selects a trajectory thatincludes the viable, but not necessarily optimal, maneuver in the nearfield that provides the greatest degree of flexibility and resilience innavigating the relatively poorly characterized far field. In thisregard, the invention is widely applicable to many planning systems.

Further, those skilled in the art will appreciate that applications ofthe invention are not limited to vehicles travelling through physicalspace. For example, the near field, far field, and composite plans neednot be spatial trajectories, and the space need not be physical, 3Dspace. The space could be a decision space, e.g. choosing a series ofapartments to rent over time, or choosing a set of jobs defining acareer path. The composite plan would then be a set of decisions, withthe most immediate decisions corresponding to the near field plan.

FIG. 8 shows a flow chart summarizing the operation of a two-stageplanning method according to the invention. Using the method of FIG. 8,a planning system selects a composite plan from among a set of candidatecomposite plans. Each candidate composite plan is formed from the unionof a near field plan, selected from among a set of candidate near fieldplans, and a far field plan, selected from among a set of candidate farfield plans.

Operation begins with the planning system obtaining measurements of thenear 110 and far 120 fields. The distinction between the near and farfields may be spatial, temporal, or both, as in the case of trajectoriesthrough physical space such as those of FIG. 4. As noted above, onaccount of its spatial or temporal proximity, the near field ischaracterized by a high degree of fidelity in the measurements obtained.In contrast, the far field is characterized by a relatively low degreeof fidelity in sensor measurements.

The planning system then determines the viability of each of thecandidate near field plans 310, and eliminates 310 from considerationthose near field plans determined to be non-viable. The planning systemperforms the viability determination using the high fidelitymeasurements of the near field.

In parallel, the planning system determines the adjacency of thecandidate far field plans 220. The planning system considers one farfield plan adjacent to a second far field plan if it is possible totransition directly from the first far field plan to the second farfield plan upon arrival at the boundary between the near and far fields.In some applications of the planning system, the adjacency of the farfield plans may possess a topology such as the microlanes shown in FIG.3, in which each far field plan, i.e. microlane, is adjacent to one ortwo neighboring far field plans. In other applications of the planningsystem, each far field plan is potentially adjacent to zero, one, ormany other far field plans. In such applications, the adjacency of thefar field plans can be summarized with a matrix A in which a_(ij)=1 ifthe ith far field plan is adjacent to the jth far field plan anda_(ij)=0 otherwise. The matrix A may be symmetric or asymmetric,depending on whether adjacency is necessarily physically symmetric innature.

The planning system then determines the viability of each candidate farfield plan 320 and eliminates 420 from consideration those far fieldplans determined to be non-viable. The planning system performs theviability determination using the low fidelity measurements of the farfield. Viability of the far field plans is thus determined based on themost easily resolved features of the far field.

The planning system then determines a flexibility score for each of thefar field plans 520 determined to be viable. In those applications whereeach far field plan has either one or two neighbors, the flexibilityscore of a far field plan may be computed as the distance between thefar field plan and the nearest non-viable far field plan. In some suchapplications, e.g. the route planning system of FIG. 7, the distance maybe enumerated by counting the number of intervening far field plans,e.g. microlanes of FIG. 7. In other such applications, the distance maybe quantified with a physical distance.

In those applications where each far field plan is potentially adjacentto zero, one or many other far field plans, the flexibility score of afar field plan may be computed as the number of adjacent far fieldplans. If the adjacency is summarized in a matrix A as described above,the adjacency of the ith far field plan may be computed by summing theith row of A.

Finally, the planning system selects the composite plan that includes aviable near field pan and the far field plan with the highestflexibility score 600. In some applications of the planning system, e.g.the route planning system of FIG. 6, each near field plan, e.g.maneuver, uniquely corresponds to a single far field plan, e.g.microlane. In such applications, the selected composite plan comprisesthe far field plan with the highest flexibility score and the uniquecorresponding near field plan. In other applications of the planningsystem, more than one near field plan may be compatible with, i.e. leadto, the far field plan with the highest flexibility score. In suchcases, the planning system can select a composite plan by comparingquantitative, scalar cost measures beyond the Boolean viable ornon-viable determination of the near field plans.

As shown in FIG. 8, the planning system obtains measurements of the near110 and far field 120 in parallel. Similarly, the planning system candetermine the viability of the candidate near field plans 310 andeliminate non-viable near field plans 410 in parallel with determiningthe adjacency of the candidate far field plans 220, determining theviability of the candidate far field plans 320, and eliminatingnon-viable far field plans 420. In an alternative embodiment of theinvention, the planning system performs these tasks in series. Inparticular, eliminating the non-viable near field plans 410 prior todetermining the flexibility score of the far field plans 520 allows theplanning system to determine a flexibility score only for those farfield plans compatible with viable near field plans. This approachreduces the computational load placed on the planning system. Thisalternate embodiment is particular useful in applications where there isa unique correspondence between near and far field plans, e.g. the nearfield maneuvers and far field microlanes of FIG. 6.

Computer Implementation

FIG. 9 is a block schematic diagram that depicts a machine in theexemplary form of a computer system 1600 within which a set ofinstructions for causing the machine to perform any of the hereindisclosed methodologies may be executed. In alternative embodiments, themachine may comprise or include a network router, a network switch, anetwork bridge, personal digital assistant, a cellular telephone, a Webappliance or any machine capable of executing or transmitting a sequenceof instructions that specify actions to be taken.

The computer system 1600 includes a processor 1602, a main memory 1604and a static memory 1606, which communicate with each other via a bus1608. The computer system 1600 may further include a display unit 1610,for example, a liquid crystal display (LCD) or a cathode ray tube (CRT).The computer system 1600 also includes an alphanumeric input device1612, for example, a keyboard; a cursor control device 1614, forexample, a mouse; a disk drive unit 1616, a signal generation device1618, for example, a speaker, and a network interface device 1628.

The disk drive unit 1616 includes a machine-readable medium 1624 onwhich is stored a set of executable instructions, i.e. software, 1626embodying any one, or all, of the methodologies described herein below.The software 1626 is also shown to reside, completely or at leastpartially, within the main memory 1604 and/or within the processor 1602.The software 1626 may further be transmitted or received over a network1630 by means of a network interface device 1628.

In contrast to the system 1600 discussed above, a different embodimentuses logic circuitry instead of computer-executed instructions toimplement processing entities. Depending upon the particularrequirements of the application in the areas of speed, expense, toolingcosts, and the like, this logic may be implemented by constructing anapplication-specific integrated circuit (ASIC) having thousands of tinyintegrated transistors. Such an ASIC may be implemented with CMOS(complementary metal oxide semiconductor), TTL (transistor-transistorlogic), VLSI (very large systems integration), or another suitableconstruction. Other alternatives include a digital signal processingchip (DSP), discrete circuitry (such as resistors, capacitors, diodes,inductors, and transistors), field programmable gate array (FPGA),programmable logic array (PLA), programmable logic device (PLD), and thelike.

It is to be understood that embodiments may be used as or to supportsoftware programs or software modules executed upon some form ofprocessing core (such as the CPU of a computer) or otherwise implementedor realized upon or within a machine or computer readable medium. Amachine-readable medium includes any mechanism for storing ortransmitting information in a form readable by a machine, e.g. acomputer. For example, a machine readable medium includes read-onlymemory (ROM); random access memory (RAM); magnetic disk storage media;optical storage media; flash memory devices; electrical, optical,acoustical or other form of propagated signals, for example, carrierwaves, infrared signals, digital signals, etc.; or any other type ofmedia suitable for storing or transmitting information.

Although the invention is described herein with reference to thepreferred embodiment, one skilled in the art will readily appreciatethat other applications may be substituted for those set forth hereinwithout departing from the spirit and scope of the present invention.Accordingly, the invention should only be limited by the Claims includedbelow.

1. A computer implemented method of determining a plan through a spacecomprising a near field and a far field, comprising: with a sensordevice, obtaining measurements of said far field and storing saidmeasurements in an electronic memory; with a processor, determining,based on said measurements of said far field, the viability of each farfield plan among a plurality of candidate far field plans; with saidprocessor, determining a flexibility score for each of said candidatefar field plans; and with said processor, selecting a composite plancomprising a far field plan having the highest flexibility score amongthose candidate far field plans that have been determined to be viable.2. The method of claim 1, further comprising: with a sensor device,obtaining measurements of said near field; and with said processor,determining, based on said measurements of said near field, theviability of each near field plan among a plurality of candidate nearfield plans; wherein said composite plan additionally comprises a viablenear field plan that is compatible with said far field plan having thehighest flexibility score.
 3. The method of claim 1, further comprising:with said processor, determining the adjacency of said candidate farfield plans, wherein a first of said candidate far field plans isadjacent to a second of said candidate far field plans if it is possibleto transition directly from said first candidate far field plan to saidsecond candidate far field plan after arrival at the boundary betweensaid near field and said far field; and wherein said flexibility scoreis based upon any of: the number of intervening far field plans betweena candidate far field plan and the nearest non-viable far field plan;the physical distance between a candidate far field plan and the nearestnon-viable far field plan; and the number of far field plans adjacent toa candidate far field plan.
 4. The method of claim 1, wherein saidcomposite plan comprises a trajectory for an autonomous vehicle; andwherein said near field and said far field comprise near and far regionsalong a driving surface.
 5. The method of claim 1, wherein saidcandidate far field plans comprise offset curves from a roadwaycenterline.
 6. The method of claim 2, wherein said candidate near fieldplans comprise a set of candidate maneuvers; and wherein each candidatemaneuver is a transition in said near field between a current microlaneand a destination microlane selected from among all microlanes,including said current microlane.
 7. An apparatus determining a planthrough a space comprising a near field and a far field, comprising: aprocessor configured for determining, based on measurements taken with asensor device obtaining measurements of said far field, the viability ofeach far field plan among a plurality of candidate far field plans; saidprocessor configured for determining a flexibility score for each ofsaid candidate far field plans; and said processor configured forselecting a composite plan comprising a far field plan having thehighest flexibility score among those candidate far field plans thathave been determined to be viable.
 8. The apparatus of claim 7, furthercomprising: said processor determining, based on measurements taken witha sensor device of said near field, the viability of each near fieldplan among a plurality of candidate near field plans; wherein saidcomposite plan additionally comprises a viable near field plan that iscompatible with said far field plan having the highest flexibilityscore.
 9. The apparatus of claim 7, further comprising: said processorconfigured for determining the adjacency of said candidate far fieldplans, wherein a first of said candidate far field plans is adjacent toa second of said candidate far field plans if it is possible totransition directly from said first candidate far field plan to saidsecond candidate far field plan after arrival at the boundary betweensaid near field and said far field; and wherein said flexibility scoreis based upon any of: the number of intervening far field plans betweena candidate far field plan and the nearest non-viable far field plan;the physical distance between a candidate far field plan and the nearestnon-viable far field plan; and the number of far field plans adjacent toa candidate far field plan.
 10. The apparatus of claim 7, wherein saidcomposite plan comprises a trajectory for an autonomous vehicle; andwherein said near field and said far field comprise near and far regionsalong a driving surface.
 11. The apparatus of claim 7, wherein saidcandidate far field plans comprise offset curves from a roadwaycenterline.
 12. The apparatus of claim 8, wherein said candidate nearfield plans comprise a set of candidate maneuvers; and wherein eachcandidate maneuver is a transition in said near field between a currentmicrolane and a destination microlane selected from among allmicrolanes, including said current microlane.
 13. The apparatus of claim7, wherein said candidate far field plans comprise segments ofmicrolanes passing through said far field.
 14. The apparatus of claim13, further comprising: said processor calculating a scalartraversability score for each of said microlanes in said far field anddetermining that the corresponding far field plan is viable if saidtraversability score is above a predetermined threshold; wherein saidtraversability score is based upon any of the roughness of a roadwaysurface along said microlanes, the curvature of said microlanes, and thepresence or absence of any obstacles along said microlanes.
 15. Theapparatus of claim 7, further comprising: said processor setting saidflexibility score to 0 for each non-viable far field plan, therebyeliminating said non-viable far field plans from further consideration;for each viable far field plan, said processor setting said flexibilityscore to one greater than the number of said candidate far field plansbetween said viable far field plan and a nearest impassable far fieldplan.
 16. The apparatus of claim 12, further comprising: for thoseinstances when two or more far field plans share said highestflexibility score, said processor selecting a composite plan bycomparing a quantitative cost of said candidate maneuver within saidcomposite plan.
 17. The apparatus of claim 16, further comprising: saidprocessor using sensor measurements to discretely characterize the nearfield terrain on a grid of cells, wherein each cell within said grid ofcells is evaluated using multiple criteria; said processor combiningsaid multiple criteria to determine a maximum traversal speed for saidcell; wherein the cost of each cell is inversely proportional to saidtraversal speed; and wherein said quantitative cost of said candidatemaneuver is proportional to the sum, along said candidate maneuver, ofthe products of said cost of each cell and the length of said candidatemaneuver within that cell.
 18. The apparatus of claim 16, wherein amongcomposite plans comprising far field microlanes with equal flexibilityscores, said processor selects the composite plan comprising thecandidate maneuver with the lowest quantitative cost.
 19. The apparatusof claim 13, further comprising: when evaluating each far field plan,said processor making a Boolean determination for the microlane withineach far field plan; wherein a microlane is determined to be eitherpassable or impassable and said flexibility score is determined for eachof said far field plans based on said Boolean determination.
 20. Theapparatus of claim 13, further comprising: when evaluating each farfield plan, said processor computing a scalar traversability score forthe microlane within each far field plan.
 21. A computer implementedtwo-stage planning method, comprising: a processor selecting a compositeplan from among a set of candidate composite plans, wherein eachcandidate composite plan is formed from a union of a near field plan,selected from among a set of candidate near field plans, and a far fieldplan, selected from among a set of candidate far field plans.
 22. Themethod of claim 21, further comprising: said processor obtainingmeasurements of near and far fields, wherein said near field ischaracterized by a high degree of fidelity in the measurements obtainedand said far field is characterized by a relatively low degree offidelity in the measurements obtained; said processor determining theviability of each of said candidate near field plans; said processoreliminating from consideration those near field plans determined to benon-viable, said processor performing the viability determination usingsaid measurements of said near field; in parallel, said processordetermining the adjacency of candidate far field plans, wherein saidprocessor considers a first far field plan adjacent to a second farfield plan if it is possible to transition directly from said first farfield plan to said second far field plan upon arrival at a boundarybetween said near and far fields; said processor determining theviability of each candidate far field plan and eliminating fromconsideration those far field plans determined to be non-viable; saidprocessor performing the viability determination using said measurementsof said far field, wherein said viability of said candidate far fieldplans is thus determined based on the most easily resolved features ofsaid far field; said processor determining a flexibility score for eachof the far field plans determined to be viable, said flexibility scoreis computed as the distance between the far field plan and the nearestnon-viable far field plan; and said processor selecting a composite planthat includes a viable near field pan and a far field plan with thehighest flexibility score.
 23. The method of claim 1, wherein the nearfield extends along a roadway from a starting transverse line through acurrent position to a first transverse line though a first futureposition at a first future time, and where in the far field extendsalong the roadway from the first transverse line to a second transverseline through a second future position at a second future time.